Column: Good Decisions. Bad Outcomes.

by Dan Ariely

If you practice kicking a soccer ball with your eyes closed, it takes only a few tries to become quite good at predicting where the ball will end up. But when “random noise” is added to the situation—a dog chases the ball, a stiff breeze blows through, a neighbor passes by and kicks the ball—the results become quite unpredictable.

If you had to evaluate the kicker’s performance, would you punish him for not predicting that Fluffy would run off with the ball? Would you switch kickers in an attempt to find someone better able to predict Fluffy’s involvement?

That would be absurd. And yet it’s exactly how we reward and punish managers. Managers attempt to make sense of the environment and predict what will result from their decisions.

The problem is that there’s plenty of random noise in competitive strategic decisions. Predicting where the ball will go is equivalent to deciding whether to open a chain of seafood restaurants on the Gulf Coast. The dog running off with the ball is the BP oil spill. When the board reviews the manager’s performance, they’ll focus on the failed restaurants. The stock is down. The chain lost money. Since the manager’s compensation is tied to results, he’ll incur financial penalties. To save face and appear to be taking action, the board may even fire him—thus giving up on someone who may be a good manager but had bad luck.

The oil spill example is an extreme case. In the real world, the random noise is often more subtle and various—a hundred little things rather than one big thing. But the effect is the same. Rewarding and penalizing leaders based on outcomes overestimates how much variance people actually control. (This works both ways: Just as good managers can suffer from bad outcomes not of their own making, bad managers can be rewarded for good outcomes that occur in spite of their ineptitude.) In fact, the more unpredictable an environment becomes, the more an outcomes-based approach ends up rewarding or penalizing noise.

In the last year I’ve asked many board members how much of a company’s stock value they think should be attributed to the CEO’s strength, and the answer is surprising. They estimate that you’ll get about 10% more stock value, on average, from a good CEO than from a mediocre one. Implicit in that estimate is the understanding that many outcomes are outside a leader’s control.

We can’t entirely avoid outcome-based decisions. Still, we can reduce our reliance on stochastic outcomes. Here are four ways companies can create more-sound reward systems.

1. Change the mind-set. Publicly recognize that rewarding outcomes is a bad idea, particularly for companies that deal in complex and unpredictable environments

2. Document crucial assumptions. Analyze a manager’s assumptions at the time when the decision takes place. If they are valid but circumstances change, don’t punish her, but don’t reward her, either.

3. Create a standard for good decision making. Making sound assumptions and being explicit about them should be the basic condition for getting a reward. Good decisions are forward-looking, take available information into account, consider all available options, and do not create conflicts of interests.

4. Reward good decisions at the time they’re made. Reinforce smart habits by breaking the link between rewards and outcomes.

Our focus on outcomes is understandable. When a company loses money, people demand that heads roll, even if the changes are more about assuaging shareholders than sound management. Moreover, measuring outcomes is relatively easy to do; decision-making–based reward systems will be more complex. But as I’ve I said before, “It’s hard” is a terrible reason not to do something. Especially when that something can help reward and retain the people best able to help you grow your business.

Dan Ariely (dandan@duke.edu) is the James B. Duke Professor of Behavioral Economics at Duke University and the author of Predictably Irrational (HarperCollins, 2008).

Articulo publicado en la edicion de diciembre 2010 de HBR.